Below we denote \(\Vert \cdot \Vert \)  as the \(L_2-\) norm for vectors. For a square matrix \(B\)  say, \(B_{\textrm {sym}}=\tfrac{1}{2}(B+B^{\prime })\)  and \(\mu (B)\)  being the largest eigenvalue of \(B_{\textrm {sym}}\) .
In the cases of (REF ) and (), [1]} consider the following assumption (recall (REF )): we have \(\mu (S)>0\)  with
\(S = \mu (S) Id\) 
